Power-law relationships (y = axb) are ubiquitous and extensively studied. The first part of my dissertation investigated theoretical and empirical power-law relationships that are drug-related. Statistical analysis and Monte Carlo simulation were used to characterize uncertainty in the allometric exponent (b) of drug clearance. While the individual b values of 91 drugs generally fell within a broad range between 0.2 and 1.2, the b value from the aggregated clearance values (adjusted to a common a value) was 0.74, with a 99% CI of 0.71 to 0.76. However, the b value for the predominantly renally excreted drugs tended towards 0.67. The simulation results suggested that the wide range of b values observed for individual drugs could have resulted from random variability in clearance values determined in the limited number of species used for each drug.; Chapter 3 characterized a novel power-law relationship. Using drug interaction information reported in 1981, 1991 and 1999, a drug-drug interaction network was described in which the interacting drugs were treated as nodes and were connected with undirected links that represented interactions. The connectivity of the resulting network followed a power-law distribution. The scaling exponent was close to −1.5 and independent of the network size. A dynamic model was proposed to account for the observed scale-free structure of the network.; Chapters 4 and 5 experimentally and theoretically explored complex interactions among pathophysiologically relevant molecules. Chapter 4 investigated dynamic interactions among the enzyme superoxide dismutase (SOD), the free radicals nitric oxide (NO) and superoxide (O2− ), and the antioxidant glutathione (GSH) in an in vitro model system. The results showed that SOD's effects on nitrosation were biphasic and dynamic in nature; i.e., while low concentrations of SOD were pro-nitrosative, high SOD concentrations inhibited nitrosation. However, even the initially inhibitory, high SOD concentrations (≥500 U/ml) became pro-nitrosative over time. SOD predominantly exhibited the pro-nitrosative effect when GSH was present. Theoretical results in chapter 5 suggested that GSH may modulate the nitrosation reaction in a switch-like manner, and that concurrently high NO and O2− generation may result in nonlinear dynamics of the nitrogen oxide species.
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机译：幂律关系（y = a x b ）无处不在并且得到了广泛的研究。本文的第一部分研究了与毒品有关的理论和经验幂律关系。统计分析和蒙特卡洛模拟用于表征药物清除的异速指数（ b ）的不确定性。虽然91种药物的单个 b 值通常在0.2到1.2之间的宽范围内，但汇总清除值中的 b 值（已调整为常见的 a 值）为0.74，99％CI为0.71至0.76。但是，主要通过肾脏排泄的药物的 b 值趋于0.67。模拟结果表明，每种药物观察到的 b 值范围很广，可能是由于每种药物所用物种的数量有限而确定的清除率值存在随机差异。第三章描述了一种新颖的幂律关系。使用1981、1991和1999年报告的药物相互作用信息，描述了一个药物相互作用网络，其中相互作用的药物被视为节点，并与代表相互作用的无向链接相连接。所得网络的连通性遵循幂律分布。缩放指数接近-1.5，并且与网络大小无关。提出了一个动态模型来解决观察到的网络的无标度结构。第4章和第5章从实验和理论上探讨了病理生理相关分子之间的复杂相互作用。第4章研究了超氧化物歧化酶（SOD），自由基一氧化氮（NO）和超氧化物（O 2 -）和抗氧化剂谷胱甘肽（GSH）之间的动态相互作用）在体外模型系统中。结果表明，SOD对亚硝化的影响本质上是双相的和动态的。即，虽然低浓度的SOD具有亚硝化作用，但高浓度的SOD却抑制了亚硝化作用。但是，即使最初具有抑制作用，高的SOD浓度（≥500 U / ml）也会随着时间的推移而变成亚硝基化的。存在谷胱甘肽时，SOD主要表现出亚硝化作用。第五章的理论结果表明，谷胱甘肽可能以类似开关的方式调节亚硝化反应，同时高NO和O 2 -的产生可能会导致GSH的非线性动力学。氮氧化物种类。
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